Invenio Imaging, a California-based diagnostic imaging company, has successfully enrolled participants for a significant trial focused on utilizing artificial intelligence (AI) technology to detect lung cancer. The trial, known as the ON-SITE study, is a collaboration with Johnson & Johnson and aims to evaluate Invenio’s NIO Laser Imaging System’s capabilities in identifying lung cancer. This innovative system is designed to provide detailed lung imaging by expediting the production and analysis of digital images.
The multi-centre trial will be conducted at two universities in Texas and North Carolina, with the goal of developing and validating an AI-based image analysis module for the NIO system. This module is intended to assist healthcare providers in detecting cancer in bronchoscopic lung biopsies, filling in the gaps where traditional rapid-on-site tissue evaluation (ROSE) is not available due to resource constraints.
Dr. Jason Akulian from the University of North Carolina expressed excitement about the potential of the NIO system to extend the benefits of ROSE to proceduralists when the service is unavailable due to staffing limitations. The device offers greater flexibility to hospital staff, enabling them to rapidly image fresh tissue biopsies without the need for staining or sectioning. This streamlined process can be carried out by existing operating room personnel, enhancing efficiency and potentially leading to improved patient outcomes.
Gustavo Cumbo-Nacheli, the principal investigator for the ON-SITE study, emphasized the transformative potential of AI in healthcare, particularly in the realm of rapid and accurate cancer detection. While still in the investigational phase, AI-powered technologies like the NIO system hold promise for enhancing patient care, optimizing cost-effectiveness, and tailoring treatments to individual patients.
In the broader landscape of lung cancer imaging, Galvanize Therapeutics recently completed patient enrolment for the AFFINITY study, focusing on the Aliya pulsed electric field (PEF) system for treating late-stage non-small cell lung cancer. Additionally, Qure.ai has received Health Canada’s Class III medical device license for its suite of medical imaging AI solutions, marking advancements in the integration of AI technology in healthcare diagnostics.
These developments underscore the growing importance of AI-driven innovations in improving diagnostic accuracy, treatment efficacy, and patient outcomes in the field of lung cancer imaging. As technology continues to evolve, healthcare providers and researchers are poised to harness the potential of AI to revolutionize cancer care and personalized medicine.